My projects include Apps I've built, Code I've written and Research I've done




Full apps and extensions I've released

The Money Trail

A Chrome Browser Extension that aggregates and allows you to explore all transactions shared by users on their Venmo Profile, to discover patterns in their spending habits.

The Marauders Map

A now defunct Chrome Browser Extension that aggregated and displayed location data shared by your friends via Facebook Messenger.

Open source code projects I've worked on

Apache MXNet

Contributed to the Apache MXNet project. Building capabilties in the deep learning framework to allow for reliable and performant deep network deployment on IoT, mobile and edge devices.

Android Location Tracker

Code for a server that automatically collects a users Android location history and exposes and API to query it, along with frontend code for a map to display location information in the browser.

Sonic Bar Code

Code from HackMIT 2013 for a server to create ultra-sonic "bar codes" associated with URLS and an iOS app capable of discovering them.

Pfast and Pfurious

Code to continuously scrape shuttle location data for the Harvard shuttles from the web app Trans-Loc.

Seam Carving

Code from my CS51 final project to resize images in a content aware manner using a seam carving algorithm.

See all my open source code on Github...

Research I've published in the fields of deep learning and digital privacy

Tensor Contraction Layers for Parsimonious Deep Nets

A paper co-authored with Anima Anandkumar and presented at CVPR 2017, introducing a new deep network "layer" based on applying the Tucker tensor contraction process to activation tensors. We find that this allows for significant dimensionality reduction of the activation tensor, yielding more efficient model representations without impacting accuracy.

Presented at CVPR 2017 Tensor Workshop

Venmo’ed: Sharing Your Payment Data With the World

A paper edited by Latanya Sweeney published in Harvard's Technology Science Journal highlighting how Venmo's default privacy settings cause users to inadvertantly publicly share a large amount of private data.

Originally published in Technology Science

Facebook's Privacy Incident Response: a study of geolocation sharing on Facebook Messenger

A paper edited by Latanya Sweeney published in the inaugural issue of Harvard's Technology Science Journal highlighting issues with Facebook's response to a privacy incident. Covered by, Forbes, The Washington Post and over 400 other global publications.

Originally published in Technology Science